LAUSR

Abstract Accommodation accounts for one of the biggest expenses while traveling, and deciding where to stay is often confusing and time-consuming. Fortunately, travelers have more options than ever before because of the substantial growth of the peer-to-peer (P2P) short-term rentals in the sharing economy. Designing a user-friendly system that considers travelers’ preferences in choosing the right accommodation can enhance customer satisfaction and increase profitability. We propose a dynamic decision support system based on the theory of multi-criteria decision making to assist travelers in personalizing their preferences and finding quality accommodations in the dominant P2P market that aligns with those preferences. We use the fuzzy best-worst method to measure the intensity of the user’s preferences and the fuzzy technique for order of preference by similarity to the ideal solution (TOPSIS) to score and evaluate alternative P2P rental properties. We present a case study in the P2P rental accommodations industry to demonstrate the applicability of the method proposed in this study.